The role of emotions in the consumer meaning-making of interactions with social robots

doi:10.1016/j.techfore.2022.121844

Technological Forecasting and Social Change

Volume 182, September 2022, 121844

https://doi.org/10.1016/j.techfore.2022.121844 Get rights and content

Under a Creative Commons license

open access

Highlights

•
3627 self-reported comments on social robots for world‑leading hotels are analysed.
•
Trust, anticipation and joy are the most frequently expressed emotions by reviewers.
•
Either positive or negative emotions influence robot sentiment polarity.
•
Joy has the greatest impact on robot sentiment polarity.
•
Anticipation and surprise do not significantly affect robot sentiment polarity.

Abstract

The interaction with social robots is supposed to be a unique and emotionally charged activity. Based on the diffusion of innovations literature, subjective feelings represent a driver of the innovation diffusion process. Yet, to date, no study has comprehensively assessed consumers' emotional responses over time to interactions with social robots. Thus, the study aims to address this research gap by combining innovation diffusion and psychology literature. The emotional content of customers' self-reported communication on social robots deployed across international hotels is categorized through Plutchik's wheel of emotions by using advanced text analytics techniques to track and analyze its evolution over time. Findings show that consumers generally express positive emotions towards social robots. Trust, anticipation and joy are the most frequently expressed emotions. Empirical results from multivariate regression analysis indicate that joy has the greatest magnitude and that anticipation and surprise do not significantly influence consumers' opinions and comments. Negative emotions are less frequent but have a significantly negative impact, which might be considered by hotel managers willing to introduce social robots.

Keywords

Social robot

Emotions

Human–robot interaction

Diffusion of innovation

eWOM

Meaning-making

Cited by (0)

Matteo Borghi is a Lecturer of Entrepreneurship and Innovation at the Henley Business School, University of Reading (UK) and a member of the Henley Centre for Entrepreneurship. He received his PhD in management from Henley Business School (UK) after earning a Master in Business Informatics at the University of Pisa (Italy) and a bachelor degree in Information Science for Management at the University of Bologna (Italy). His research lies at the intersection of data science, management and entrepreneurship, with special reference to the impact of Industry 4.0 technologies on digital business modelling and e-Reputation of companies in services industries.

Marcello M. Mariani is a Full Professor of Entrepreneurship and Management at the Henley Business School, University of Reading (UK) and the University of Bologna (Italy), as well as a member of the Academy of Management and the European Institute for Advanced Studies in Management. His current research interests include big data and analytics, eWOM, digital business models, AI, robotics, IoT, and interfirm relationships. His research has been published in Technological Forecasting and Social Change, Harvard Business Review, MIT Sloan Management Review, Industrial and Corporate Change, Long Range Planning, Journal of Business Research, Industrial Marketing Management, Production Planning & Control, Psychology & Marketing, Journal of Advertising, International Journal of Electronic Commerce, European Accounting Review, and more.